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Model predictive control with dynamic move blocking
Model Predictive Control (MPC) has proven to be a powerful tool for the control of systems with constraints.
Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning
Two established approaches to engineer adaptive systems are architecture-based adaptation that uses a Monitor-Analysis-Planning-Executing (MAPE) loop that reasons over architectural models (aka Knowledge) to make adaptation decisions, and control-based adaptation that relies on principles of control theory (CT) to realize adaptation.
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